Analysis of locational advantages of host countries as
determinants of the distribution of outward FDI of Dutch
Multinational Enterprises
By: Adriaan van Heyningen Nanninga Studentnumber 1227688
TABLE OF CONTENTS
ABSTRACT 3
SECTION 1: Introduction 4
SECTION 2: Dutch economy and Dutch FDI outflow 7
SECTION 3: Literature review on the determinants of FDI attraction 11
SECTION 4: Hypothesis and research questions 19
SECTION 5: Data and methodology 23
SECTION 6: Empirical results 28
SECTION 7: Conclusion 32
REFERENCES 35
ABSTRACT
SECTION 1: Introduction
In the light of the growing amount and importance of FDI outflows from Dutch firms the primary objective of this research is to develop a better understanding of which locational advantages of host countries Dutch MNEs take into account when deciding where to allocate their FDI. With this research I want to obtain insight in the relative importance of those variables, to give an explanation for the observed relationships and observe what factor(s) might be the key reason for Dutch firms to invest in a certain country.
FDI is an activity in which an investor resident in one country obtains a lasting interest in, and a significant influence on the management of, an entity resident in another country. This may involve either creating an entirely new enterprise (so-called “greenfield” investment) or, more typically, changing the ownership of existing enterprises (via mergers and acquisitions). Other types of financial transactions between related enterprises, like reinvesting the earnings of the FDI enterprise or other capital transfers, are also defined as foreign direct investment. (OECD Economic Outlook No. 73, Chapter 6, 2003).
The amount of FDI has increased at a very rapid pace during the past 25 years. Due to the increasing globalization and ongoing tariff reductions, international trade has been greatly promoted during the past few decades. Exporting often goes hand in hand with high transportation costs and trade barriers, so FDI is a good alternative to these inherent costs. On top of that, firms in the service sector often need to be close to their customers, making it necessary to relocate themselves. Entering foreign markets has become much easier which increased opportunities for MNEs. Figure 1.1 depicts the rapid increase in world total outward FDI.
multinationals are diversifying over a larger range of countries and taking a bigger and bigger share of the total amount of output of these countries for their account.
The amount of international production also portrays the importance of FDI for individual countries. This has expanded greatly during the past two decades. International production is the production located in a certain country, whilst it is not controlled by a company from the same country. It is under control of a company with its headquarter in a different country and is usually financed by FDI.
Despite its increase, FDI is still unevenly distributed across the world. Also, over the past two decades there have been several significant changes in the geographical distribution of FDI. This occurred both within the developed and developing countries and between them (Dunning, 1998) (see figure 1.2 and 1.3). The bulk of FDI is among the developed countries. The developed countries were responsible for 81% of total world inward FDI flow (2000) and 70% of total world inward FDI stock (2000). Over time this distribution has shifted. Two decades ago the concentration of inward FDI amongst the developed countries was even higher than today, respectively 86% of world FDI inward flow and 75% of world FDI inward stock. The fact that developed countries attract such a large portion of the outward FDI by the rest of the world suggests that there are certain factors in the developed countries that play a large role in attracting FDI. It also suggests that, in general, companies are much more inclined to invest in developed countries. Outward FDI is therefore very likely to be influenced by a certain range of factors existent in developed countries that developing countries lack or developed to a lesser extent.
Since the introduction of Dunning’s OLI (Ownership, Locational and Internalization advantages) model1 various economists have looked into FDI and its distribution patterns. It appears that Dunning’s model, first proposed in 1977, is still the most influential model in explaining modern day FDI flows. As is clear from table 1.1, all variables used in research on FDI patterns can be covered by one of the OLI factors, with most of them impacting locational advantages.
Despite the fact that a vast amount of research exists on the variables affecting FDI distribution in general, little research has been executed on the specific case of The Netherlands. The Netherlands poses an interesting case. It has one of the highest ratios of outward FDI over GDP (Figure 1.4). In terms of population size, physical size and economical terms, The Netherlands is a small country. As small countries generally have limited resources and are dependant in various ways on foreign trade, the Netherlands has been building up world-wide presence since the 17th century. Important pioneers in this sense have been the Dutch East India Company (VOC) and the Dutch West Indies Company (WIC). International trade has always been high on the agenda of Dutch policy makers and still is today. As part of the European Union, the Dutch economy is an open economy very much dependent on international trade. With the port of Rotterdam as a gateway to the rest of Europe and Schiphol as an international hub, it is a key entrance to the European mainland.
In this thesis, I will investigate the host-country-specific determinants of Dutch outward FDI flows by analyzing the values of the determinants of a set of 49 different host countries over a time-period of 21 years (1985-2005). The aim is to develop a better understanding of what factors of host countries are able to influence the amount of inflowing FDI from Dutch MNEs. Secondary objective of this research is to compare the results of this research to the results of general literature on the subject. Are the results in-line with general literature on this subject? If not, where do they differ and why? Could the specific characteristics of the Dutch economy – described later on in this thesis - possibly provide an explanation of why we observe differences? To meet the aims, I will try to answer the following research question:
“What are the locational factors that play the most profound role in determining where Dutch MNEs perform their outward FDI?”
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SECTION 2: Dutch economy and Dutch FDI outflow
Below I will outline some characteristics of the Dutch economy in its relationship to outward FDI to try to understand why the distribution of Dutch outward FDI across host countries might differ from the general patterns found in literature. The Netherlands has among the highest ratios of outward FDI to GDP. It is important to understand what drives this high ratio of outward FDI to GDP to try to understand whether those factors could possibly impact the way that Dutch FDI decisions are made.
- The Netherlands is a small and open economy very much dependent on the rest of the world.
In their paper, Hoesel and Narula (1998) discuss the fact that small open economies, such as that of the Netherlands, tend to be much more internationalised. A relatively large share of their value added activity is being performed with the explicit purpose of serving overseas markets. The opportunities for expansion are soon exhausted in a small market, and this provides the stimulus for creating multinationals. Furthermore, the Netherlands has an open economy. In comparison with other countries it has relatively few hindrances to the flow of capital, labour and raw materials. Local opportunities are limited. Due to the small home market Dutch firms will actively look for new markets to supply and look for opportunities on how to increase economies of scale and scope. For certain Dutch firms the limited amount of natural resources is the direct stimulus for looking for international expansion.
- Dutch MNEs are knowledge seekers
In the Netherlands, most of the R&D is performed by only a small number of MNEs. Because of its small size, the Netherlands covers only a limited range of technological sectors in substantial detail. Business R&D is carried out on a relatively small scale and at low intensity (Van Hoesel and Narula, 1998). The bulk of Dutch R&D is performed by only five large companies, namely: Shell, Akzo-Nobel, DSM, Unilever and Philips.
Technology spillovers in places such as Silicon Valley are one of the many examples of the benefits that competition might have. Having said this, it is very much likely that Dutch firms are knowledge seekers rather that knowledge owners. Dutch MNEs are likely to invest in countries where they can benefit from technological development spillovers from other companies. For certain Dutch MNEs the factor of the possibility to benefit from technological development spillovers will play an important role in deciding in which host countries to invest in. Because of the limited scale and scope of the Dutch R&D expenditure, they are required to benefit from new technology developed abroad rather than develop it in the Netherlands itself. The fact that the Netherlands only has such a small number of MNEs might induce them to invest in countries where economies of scale and scope are more existent. By doing so, they are much more able to benefit from other companies’ R&D investments.
- The Netherlands’ low labor productivity
Kleinknecht and Naastepad (2005) found that in the Netherlands, the more flexible labor relations and reduction of wage-cost pressures created a high growth rate of jobs. The other side of the coin meant that consequently, there have been negative incentives to labor productivity growth and innovation. The Dutch government aimed for a long period of time to increase the amount of employment after the recession in the early 1980s. They indeed succeeded at this, and where able to achieve full employment when neglecting structural/ hidden unemployment in the Netherlands by the end of the 1990s.
The high employment growth did come at a cost. Labor productivity grew at only a very modest pace, which resulted in low innovation. So in order to increase the amount of innovation and productivity, Dutch MNEs started to look over the Dutch boarders. Therefore, Dutch firms can be expected to look at countries where productivity growth is higher than domestically and where competitiveness due to the opening up of foreign boarders will be able to promote innovation.
- High dependency of services economy
the service sector plays quite a large role (figure 2.1). The amount of outward FDI is substantial, and has remained fairly stable around 65%.
The share of services in a country’s economy is often related to the level of development of this economy. It could be interesting to investigate whether the dependency of services economy impacts Dutch outward FDI strategies. In this context, it is interesting to observe how a service-oriented economy allocates its outward investments.
- The impact of globalization on Dutch MNEs FDI decisions
The internationalisation of the Netherlands has become an important source of the growth of Dutch MNEs. “Internationalization of production helps to better exploit the advantages of enterprises and countries, increase competitive pressures, …. , and stimulate technology transfer and innovative activity” (OECD Economic Outlook No. 73, 2003).
In the internationalization process, foreign direct investment (FDI) has played an important role. In the past few decades, outward FDI for the Netherlands has been very high relative to the rest of Europe and various other OECD countries. It has had the highest share of FDI/GDP of Europe in both the 80’s and 90’s (figure 1.4), with an increase from around 28% in the 1980s to 41% in the 1990s. This finding indeed proves the point made earlier, that the Netherlands relies to a large extent on foreign influences and needs foreign countries’ influences for its development. The Dutch leading companies in terms of outward FDI are much more able to reach their full potential by benefiting from opportunities that arise abroad. By doing so, they do not rely purely on their limited local market but are able to grow by expanding themselves over the boarder. The fact that the outward FDI rate is so high for the Netherlands shows that Dutch firms’ growth rates are very much influenced by their cross-boarder performance.
In line with the above findings, the ratio of exports and imports over GDP of the Netherlands (the measure for openness of an economy) is also substantially larger than in the case of large economies. In the 1990s, the OECD has estimated that exports and imports as a share of GDP was nearing 50% in the case of the Netherlands compared to averages of 20% for Germany, France and the UK (Hogenbrink and Narula, 1999).
Having established the importance of FDI and foreign trade for a small country such as the Netherlands, one has to observe what the consequences are of this with respect to their investment decisions abroad.
SECTION 3: Literature review on the determinants of FDI attraction
This section provides a brief review of existing theoretical and empirical research on the determinants of FDI attraction. It focuses on the following three issues:
- What potential factors determine the attractiveness of countries in terms of FDI location?
- What variables have the most effect in influencing the distribution of FDI?
- What factors influence Dutch outward FDI decisions?
What potential factors determine the attractiveness of countries in terms of FDI location?
FDI by any multinational enterprise generally arises from the fact that a firm possesses some kind of advantage such as being able to benefit from economies of scale due to lower costs or a superior technology or access to new markets. If an MNE is exactly identical to a domestic company, entering a foreign market would not be profitable. There are inherent costs to enter a new market, such as transportation costs, working under new governmental laws and the fact that language barriers could arise. So in order to invest abroad, various conditions should be met.
John Dunning (2001) has proposed a framework on why firms invest abroad. He has created the so-called OLI framework, in which he suggests that firms base their investment decisions on three factors, namely: Ownership, Location and Internalization. His theory was first proposed in 1977 and later reassessed in 1981. In one of Dunning’s later papers (Dunning, 2001), he proposed that production financed by FDI and undertaken by MNEs will be determined by the configuration of three sets of required factors:
2) The extent to which firms choose to locate these value-adding activities outside their national boundaries. (Location advantages)
3) The extent to which firms perceive it to be in their best interests to internalise the markets for the generation and/or the use of these assets; and by doing so add value to them. (Internalization advantages)
The variables that can be included in each of the three factors can be numerous. According to Dunning, the location variable can for example include labour costs, tariff barriers, and the presence of competitors or agglomerative economics. Because of this large amount of possible influences on the three forces, the model has received a substantial amount of criticism. The amount of variables being able to influence the decisions to invest in a certain country make it hard, critics say, to determine the predictive value of the model. However, this doesn’t mean that there is no relevance to the model. There is sufficient statistical proof that there is indeed a certain set of variables that drive the foreign investment decisions of MNEs. There have been various empirical investigations on the OLI model, a few of which will be discussed now and in the remainder of this chapter.
Hong and Chen (2001), for example, argued that the Location variable in Dunning’s OLI model for China is a function of GDP, the weighted average wage rate between China and other countries, and the relative economic increase rate between China and other countries based on a sample of 12 countries for a period of 13 years. In their model they used one year lags, so they argued that current year’s FDI is explained by previous year’s factors. Their finding provided enough evidence that the three explanatory variables in the model are major determinants of the Location-specific advantages in China during the period 1985 until 1997. A similar test was performed on the relationship between China’s imports and exports in relation to FDI, which also showed a prominent and positive relationship to FDI.
As Dunning stated, his OLI model was not designed in order to develop a complete and full explanatory framework which includes all of the possible variables that determine the amount of FDI by MNEs. It was designed to create a small set of forces that are, each in their own way, explanatory factors of FDI. Because there are so many factors that could potentially influence FDI, it is hardly possible to give a total and complete explanation of this.
In the OLI model, the Ownership and Internalization variables are primarily aimed at explaining the factors of why MNEs decide to perform cross-border investment activities. It is a fact that ownership variables have greatly affected the significant rise in global FDI patterns. The value of international merger and acquisition has increased around ten-fold during the 1990’s (Di Giovanni, 2003), which has been an important influence on the growing global FDI rates. The location factor in the model however is aimed to explain why an MNE chooses a specific country to invest in (the attractiveness of a country). Consequently, we should look into the location factor to get a better understanding of why Dutch MNEs FDI is directed at certain countries and not to others.
To get a better understanding of the underlying variables that influence the location factor, there are various studies that are of interest. Michalet (2000) has taken a sample of almost one hundred companies from the United Stated, Europe and Japan and belonging to 7 different industry groups (namely chemicals, electronics, electrical equipment, telecommunications, hotels, textiles and apparel, and automotive and vehicle parts) and performed studies on them with respect to their (international) strategies. He performed his analysis by means of interviews with managers from all of the companies in terms of what they though made a country attractive and why they investment in which countries. This was done by scaling companies from 1 to 5 and performing an open-questionnaire. By doing so, not only was his study based on figures, also the motivations behind the companies’ decisions where included.
The institutional background of an attractive investment climate
For an attractive investment climate the following three institutional prerequisites have to be fulfilled:
- Political and macroeconomic stability: Investors are generally deterred by risk; moreover, they need to be able to evaluate their investment return on a medium to long-term period.
- A transparent, stable, and non-discriminatory legal and regulatory environment.
- Bureaucratic procedures and institutional rigidities must be banned. MNEs generally want a free foreign exchange regime with repatriation and a flexible labour market. Bureaucratic procedures and its usual informal "payments" such as bribes are sometimes considered to be the price to pay for having access to the domestic market and for benefiting from a more advantageous position due to the existing level of tariff barriers. Global investors need free trade, on the one hand, to maximize economies of scale generated by manufacturing in different sites and in various countries and, on the other, by exporting to the world market. Transaction costs have to be as small as possible.
The economic and social background
According to Michalet, the economic and social background becomes important for a global investor when the conditions for a good institutional background have been met. Next, to decide to which country to direct FDI funds, a global investor compares what he needs to start a profitable activity to what factors the country is offering. At this stage he will compare the local advantages of host countries for his FDI. The five main criteria – economic and social - for a comparative local advantage are the following:
markets, but large regional markets because of their free access to other members of the European Union.
- An efficient communication system. This is a key factor for MNEs to efficiently operate far-flung subsidiaries in the rest of the world, as well as the home office.
- Qualified labor is another major attractive advantage from a global investors’ viewpoint. As it usually was cheap labor to be an important factor that attracts investors, nowadays qualified labor is a major consideration. Nowadays it is often the case that the technology used abroad is more sophisticated than in the home country due to the fact that the plants are more recent and embody the latest technology.
- The presence of efficient local firms. This seems to be an expansion of the previous argument, but it is in fact covering an increasingly important dimension of a country’s attractiveness value. Very efficient local support industries are defined by their capacity to meet the needs of subsidiaries in terms of technical specification, quality for product, and delivery time.
- Privatization programs are also considered as an investment opportunity, and to a lesser extent, fiscal incentives such as tax holidays and subsidies have been considered to be a factor that can enhance a country’s attractiveness.
What variables have the most effect in influencing the distribution of FDI?
Having established what theoretically influences the attractiveness of a country and how policies can affect the in- and outflow of FDI, various studies have been performed in order to determine the empirics of certain variables and their relationship to FDI.
that it is the greatest determinant of FDI in their study. Other variables that greatly affected the outflow of FDI to a certain country were GDP growth, real GDP per capita growth, the level of human capital and openness.
Morrissey and Rai (1995) have also claimed that the size of a market as well as the growth potential is very much taken into account when investors relocate production into host countries. This was further confirmed by the UNCTAD (2004), who state that overall there is a stable and positive relationship between global FDI flows and world GDP growth. According to them, on the supply side, FDI is affected by the availability of investment funds from corporate profits or loans, which in turn are affected by domestic economic conditions. On the demand side, growing overseas markets lead TNCs (Trans National Companies) to invest more, while depressed markets inhibit them.
There are various reasons why FDI can be a result of lagged FDI, or agglomeration effects. The global relationship between the two factors was part of the studies of Braunenhjelm and Svensson (1996), Campos and Kinoshita (2003) and Agiomirgianakis (2006). Cheng and Kwan (2000) observed the relationship within China and how FDI is distributed through China. From all four studies, in their own contexts, there was sufficient proof that a general relationship exists between the amount of FDI stock and FDI flows. Whenever a country or region shows large inflows of foreign capital, the next period will generally be a function of the previous periods’ stock of FDI. The main argument for this observation is that being less knowledgeable of a country’s environment, foreign investors may view the investment decisions by others as a good signal of favourable conditions and invest there too, to reduce uncertainty (Campos and Kinoshita, 2003). This argument on positive externalities is based on three main motivations:
- Technology spillovers can be shared among foreign investors among various industries. How to operate in a host economy comes from direct experience of investors
- Industry-specific localization arises when firms in the same industry draw on a shared pool of skilled labour and specialized input suppliers.
- Economic geography emphasizes backward and forward linkages as a source of agglomeration.
play an important role in the investment decisions. On the other hand, his findings did provide proof that trade (due to openness) had a positive effect on the outflow of FDI. Although his motivation for the lack of a relationship between the skill endowment and FDI is limited, it is an indication of the fact that Dutch MNEs do not consider skill endowments to be a substantial factor in determining in which country a MNE invests. Cheng and Kwan (2000) found similar results for the Chinese economy. They found that none of the educational variables (measured as a percentage of the population with primary and higher education) has a positive effect on the level of FDI inflow to the various regions of China.
Finally, Gholami, Lee and Heshmati (2005) have investigated the relationship between the openness of a country (measured in terms of imports plus exports as a share of GDP) and its relationship with FDI. Their findings revealed that for a range of 17 countries (the Netherlands was not included in the sample), there was a positive relationship between the two factors. As mentioned above, this view was also shared by Agiomirgianakis, Asteriou & Papathoma (2006).
So all in all (as evident from table 1.1), there is empirical evidence of a general relationship between FDI and various factors. The most commonly investigated relationships with FDI concern, among others, the variables: GDP growth, GDP per capita, lagged FDI, and openness. But do these factors also explain why Dutch firms perform their cross-border investments in a similar pattern, given the specific characteristics of Dutch FDI described before? Do Dutch firms invest abroad based on similar motivations as do other MNEs? Does the fact that only a small number of MNEs are existent in the Dutch economy create a different pattern of outward FDI? And are the predictions made by various economists of the effect of various variables on the distribution of FDI also applicable to Dutch MNEs?
What factors influence Dutch outward FDI decisions?
Vos and Sanchez (2004) have empirically found that the Dutch MNEs FDI decision is based on three main criteria. Dutch Firms’ decisions to invest abroad are related to:
- The potential of efficiency gains and competitive environments for their (mostly) export-oriented production
These factors have played a large role in the increasing amounts of FDI during the 1980s and 1990s.
SECTION 4: Hypotheses and research questions
Given the existing findings in literature on outward FDI flows and the characteristics of the Dutch economy, the factors GDP growth rate, GDP per capita, openness and WTO membership could be important in FDI outflow decision making. Based on these factors four hypotheses have been developed for testing to try to answer the general research question of this thesis:
“What are the locational factors that play the most profound role in determining where Dutch MNEs perform their outward FDI?”
As past research shows, the level of growth of an economy can positively influence the amount of FDI inflow in that country.
The growth rate of a country’s economy and the FDI flowing into the country seem to be very much interrelated, i.e. one promotes the other. On the one hand, FDI inflow promotes output levels in the host economy. On the other hand the level of economic development, as a determinant, plays a significant role in attracting FDI (Agiomirgianakis, Asteriou and Papathoma, 2006).
As mentioned before, Morrissey and Rai (1995) as well as UNCTAD (2004) argued that there is a positive relationship between global FDI flows and world GDP growth. Consequently, it is therefore very much expectable that MNEs from the Netherlands consider the amount of growth of an economy and its prospects to be an important factor in determining where to invest in.
Michalet’s (2000) finding that big and growing markets are an important aspect in the relocation of FDI is further proof that, in general, firms analyse these variables before deciding where to put their investments.
it is essential therefore that amongst other conditions the foreign market is one with solid growth prospects.
H1: There is a strong and positive relationship between Dutch outward FDI and host country’s GDP growth rate
As mentioned before, the level of GDP per capita (as well as the GDP growth rate) is a good indicator for the level of development, the size of a market, and the growth potential of a country. GDP per capita is often included in studies on FDI, as it is a measure of income and demand in a country (UNCTAD, April 2006).
The various studies mentioned have provided sufficient belief to that this will create a positive effect on FDI. As was argued by Michalet (2000), high FDI rates are positively correlated to big and growing economies. Such an economy will most likely exhibit growing GDP per capita rates. It is expected that Dutch firms also take the aspect of GDP per capita into account when making allocation decisions regarding FDI.
H2: There is a strong and positive relationship between Dutch outward FDI and host country’s GDP per capita
Several studies exist on the relationship between openness and FDI inflow. In most cases, it is assumed to be a positive influence on the amount of inflow of capital into a country. Openness of an economy is often measured by the amount of exports and imports as a share of GDP. Openness is a function of the amount of trade restrictions present in a country which directly influence export and import levels.
The reason for a potential relationship to exist between the two variables is that economies in which trade is important also have relatively higher FDI (Gholami, Lee and Heshmati, 2005). A country with high exports and imports, relative to its GDP level, should consequently also prove to be a good location for FDI.
and the fact that in most cases a positive relationship is indeed visible for a large range of countries (Culem (1986), Hong and Chen (2001), Tuman and Emmert (2003) and Foldvari (2006), among others), it can very much be expected that countries with high imports and exports relative to their GDP levels will attract a higher fraction of FDI of Dutch companies’.
H3: There is a strong and positive relationship between Dutch outward FDI and a host country’s openness
Another indication for the openness of a country’s economy is whether or not the country takes part in international trade agreements. Trade agreements make it easier for countries and companies to trade with each other. Membership of trade agreements often coincide with the reduction of trade restrictions.
The WTO was established in 1995 with the objective to improve and stimulate international trade. By means of multilateral negotiations, the terms of trade of a large range of issues are discussed, ranging from agriculture to anti-dumping policies. Although negotiations are often long and complex, various agreements are made in order to make trade fairer for all of the parties involved and to remove trade barriers around the world. To achieve its objective the WTO performs the following functions2:
- Administering WTO trade agreements - Forum for trade negotiations
- Handling trade disputes
- Monitoring national trade policies
- Technical assistance and training for developing countries - Cooperation with other international organizations
The fact that a large range of countries are involved in the negotiations of the WTO (149 countries at the end of 2005) means the impact of the WTO is large and should have a noticeable impact on cross-boarder activity increase amongst its membership countries. The Netherlands is also a WTO member. Consequently I expect other WTO member countries to obtain larger
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inflows of FDI from the Netherlands than non-members and that once membership is obtained FDI from the Netherlands will increase.
The impact of WTO membership could be especially important to Dutch MNE’s due to The Netherlands relatively high dependency of the services industry. In order to be competitive in a foreign market, a service provider requires to have physical presence in that market. Whereas a manufacturer of goods can have access to foreign markets by exporting, service providers have to be closer to their consumers. So for service provides there is a greater need to set-up subsidiaries in foreign markets in order to grow abroad. It is very likely that Dutch firms will want to establish themselves in markets where trade restrictions are limited due to WTO membership.
SECTION 5: Data and methodology
In this section I will empirically assess the determinants of outward FDI of the Netherlands to various host countries. The equation explained in the remainder of this section will be estimated using Generalized Least Squares (GLS), which will compute the parameters of the regression equation. A GLS analysis will be performed because the Ordinary Least Squares (OLS) analysis assumes that country specific effects are not of influence on the relationships. However, as I will explain later, there are indeed country specific effects on the destination of Dutch outward FDI. I will perform the analysis using a fixed-effects dynamic panel model. The fixed-effect model shows whether or not the observations have produced an effect on the outcome of the regression result. This model uses fixed effects, because it assumes the country specific effects are fixed. This is indeed the case, because these effects are based on the values existent in the Netherlands. Obviously, these are the same irrespective of the destination of the FDI. The variables for which this will be the case will be discussed in further detail in the remainder of this chapter. The model uses panel data because the dataset contains observations on multiple variables observed over multiple time periods. In total 49 host countries are included in the analysis and the regression analysis will cover the time period of 1985 until 2005.
The first important observation is the level of multicollinearity between the variables (table 5.1). This is relatively low for all of the concerning variables, so this is not a concerning factor in the analysis. If multicollinearity would exist, it could have been a distorting factor to the GLS. As is clear from table 5.1 though, the extent to which it exists in this analysis is fairly limited and so GLS remains a sufficient mean of analyzing the data.
In order to answer the hypotheses discussed in section 4, I constructed the following regression equation which I will use to empirically assess the research question.
Δ(FDI) i,t= β0+ β1GIi,t-1+ β2y i,t-1+ β3Open i,t-1+ β4WTOi,t-1- β5Distancei + β6Sizei + β7GINLt-1
+ εit
real GDP (GI), the country’s GDP per capita (y), the country’s openness (Open) measured in terms of (imports + exports)/GDP and membership of the World Trade Organization (WTO).The WTO membership in this analysis is treated as a dummy variable. This means that this variable will have the value of 1 when a host country is a WTO member and 0 when it is not. I have included the physical distance from the Netherlands (Distance), the geographical size of the host country (Size) and the growth rate of the Dutch economy (GINL) as control variables. The Dutch economic growth variable is the same for each country to which the FDI is directed. Therefore, these variables are considered to be fixed, which explains the use of the fixed effects model. Because physical distance and host country size are country specific, the use of GLS is preferred over OLS. The remaining items in the equation, β0and ε, are a constant and an error term.
The monetary values used for this analysis are expressed in Euros in real terms. This means that the amount of Dutch outward FDI and the GDP per capita are all expressed in Euros.
FDI
This is the dependent variable in the equation which I hope to explain by using the mentioned independent variables. FDI is measured as the total amount of capital that Dutch firms have invested into a certain country at a certain moment in time. Therefore, the values include the amount of profits made in a country that are then reinvested, but do not include the profits made which are sent back to the mother company in the Netherlands. The value of Δ(FDI) i,t indicates the change in FDI stock from year t-1 to t for a specific host country.
The level of correlation is an indication of the strength of the relationship between the dependent and an independent variable. The data for the Dutch outflow of FDI is obtained from the statistical database on the website of de Nederlandse Bank3. In the database, the data concerning outward FDI stocks are denominated for each year since 1984. The data is denominated in Euro terms.
Through this data, it is possible to determine how much capital Dutch firms have invested in each country, but not how much capital each individual firm has invested. Therefore, no distinction is
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made between whether one firm has invested the total amount of capital in that certain country, or whether there have been many firms each investing a fraction of the total amount.
GDP growth
GDP growth rate data are obtained through the International Monetary Fund4. In the statistical database available on the website each country’s real GDP as well as their GDP growth rates, measured as the percentage change of the GDP value to the GDP value of the previous year are published. The values that are published are in local currencies.
GDP per capita
The data for this variable is also obtained from the statistical database on the IMF website. The definition of GDP per capita used by the IMF is GDP in terms of constant price dollars divided by the total population of the country in a certain year. Therefore, this value is influenced by both the level of GDP as well as the total population (including migratory factors). Since values are published in constant price dollars it was relatively straightforward to obtain the required data from the database and include them in the model. The IMF database included all of the countries included in the analysis, with publications starting in 1980. Therefore, 1980 is the base year for the analysis.
To some extent, the level of GDP per capita corrects for size. As I will discuss later on, a size variable is included to observe the amount of physical opportunities in a country. However, this is also very much dependant on the level of development of a country, measured by GDP per capita.
Openness
The openness variable is calculated as the total amount of exports and imports, as a share of GDP. The data used is obtained through the World Trade Organization5. These values are published in Dollars and are consequently calculated as a fraction. Low values means that the country in question is considered to be a relatively closed country whereas high values mean a country is relatively open. Having said this, I expect the countries with high values to correlate positively to the outflow of Dutch FDI to that country.
WTO membership
4 www.imf.org 5
This final variable is also obtained through the WTO website. As WTO membership is a dummy variable, 1 means a country is a member and 0 means the country is not. Because the WTO was only established in 1995, this variable will not give any results before this period. Most of the countries included in this analysis have joined the WTO once it was established, so it is particularly interesting to observe what its effect has been in the period when it was established.
Distance
This variable is the physical distance from the Netherlands to a country measured in kilometres. The distance is measured from capital city to capital city to avoid that values for neighbouring countries to be 0. The expectation is that the further away a country is, the less likely Dutch companies are willing to invest in them.
Size
The size variable is based on a country’s geographic size measured in squared kilometres. The larger the area of a country, the more physical opportunities are available for investments. In that sense, this variable is added as a control variable.
Dutch economic growth
Last but not least, it is worth the investigation to see whether or not the performance of the Dutch economy itself has any effect on outward investments. This relationship is expected to be positive, because when more capital comes available in the home economy, it could lead to increased investments abroad. This value is obtained from the same IMF database mentioned earlier. As a final control variable, it is interesting to observe its effect on the relationship as a whole. This variable is measured as the percentage change of GDP from one year to another.
As the regression equation shows, I expect the value of Dutch outward FDI to certain countries to be positively related to all of the explanatory variables, except for the control variable Distance. This is so, because investments are more likely to be made close to home, as it will allow better control. The motivations behind the other variables have already been discussed in the previous sections.
observations of the variables. Consequently, we can see the effect of changes in these variables on the flows of FDI to and away from the Netherlands to that country.
In total 49 host countries6 are included in the analysis. The countries included in this analysis account for 80-90% of the total amount of outward FDI by the Netherlands per year. Consequently, a very substantial share of the total outward FDI is included in the analysis. The selection of host countries included in the analysis was made based on the availability of the required data for the regression analysis. The countries included in the analysis had to fulfil the data requirements completely. Only for the selected 49 countries all required (longitudinal) data inputs were available. The reason for taking such a large range of countries is to get the most accurate results on the relationship. The countries included in the analysis are both developed and developing countries, including various high potential countries (China, India, and Brazil). By doing so, we get a clear view of what factors Dutch MNEs find relatively more important. By taking a smaller range of countries, this will create a bias towards those countries and it will be more difficult to come with a general conclusion on the effects of the variables on Dutch MNEs investment decisions. For these countries, Dutch FDI outflow is available for the whole period between 1984 and 2005. Because the analysis will be performed using FDI outflows at period t in relation to variables in year t-1, this means that our starting date for measurements is in 1985. Consequently, the analysis will be based on 21 yearly observations. Because of the lag used in the analysis, I argue that the investment decision at point t is the direct result of the variables in period t-1. Due to this introduction of lagged FDI, I will lose one year for the analysis. I make use of this large dataset using longitudinal data, as it will give the most accurate results. By doing so, it will become clear whether yearly changes of certain variables will have a direct effect on the amount of FDI flowing from the Netherlands to certain countries.
The various studies performed on the issue of host country locational advantages in attracting FDI include a large range of variables that potentially affect the level of FDI attraction. There is not much point in discussing them all. For some of them previous research has indicated a lack of relevance. Others are interrelated to the variables used in the analysis of this research. For those reasons and the motivations for using the variables discussed in this paper, I will limit myself to only a limited number of potential variables affecting FDI.
6
SECTION 6: Empirical results
The model used for this analysis is explained in detail in the previous section. From the results obtained from running the regression analysis based on the equation described in section 5 various conclusions can be drawn. For a complete overview of the results of the analysis see table 6.1 in the appendices.
Dependant variable: (FDI outflow)i,t
Sample: 1985-2005
Variable World Europe Africa Asia AmericaNorth AmericaSouth Constant -98,12 3666,89 -303,90 -53,28 -125337,47 89,84 (-0,42) (4,18)*** (-1,60)* (-0,63) (-0,75) (0,26) GIi,t-1 12,75 25,39 10,17 -4,71 158,93 14,97 (0,70) (0,53) (1,12) (-0,90) (0,47) (1,65)** y i,t-1 3,29 -1,60 -5,96 0,22 -5,85 0,36 (4,72)*** (-1,26) (-1,50)* (1,02) (0,40) (0,36) OPEN i,t-1 -171,31 -2666,38 4,52 34,16 -16905,61 -2,98 (-1,26) (-3,15)*** (0,02) (1,09) (-1,27) (-0,04) WTO i,t-1 489,12 1522,47 130,41 68,58 5103,32 39,96 (3,41)*** (4,96)*** (2,43)*** (1,51)* (1,78)** (0,49) Distancei -0,04 -1,42 0,04 0,01 12,56 -0,01 (-2,40)*** (-4,97)*** (0,78) (1,00) (0,74) (-0,47) Sizei 0,04 -0,12 0,12 0,02 5,49 0,04 (1,53)* (-0,15) (1,64)* (1,87)** (0,77) (2,77)*** GINL t-1 42,59 -159,97 17,88 2,24 1283,34 -20,83 (-0,78) (-1,49)* (0,89) (0,13) (2,28)** (-0,66) R² 0,06 0,12 0,14 0,03 0,18 0,08 Adj. R² 0,05 0,10 0,07 0,01 0,07 0,04 Observations 1029 399 84 336 63 147
Note: t-statistics are reported in parentheses.
***, **, * denote that the coefficient is significant at 1, 5 and 10 percent level of significance.
I was hoping to prove that the GDP growth rate would play a decisive role in attracting and positioning FDI, hypothesis 1. Market capacity permits potential economies of scale exploitation and standard production factor specialization, and so a significant relationship was expected with FDI flows. However, the statistics do not provide enough proof with this relationship to accept.
One observation with respect to the GDP growth variable is the positive correlation found for the South-American continent in the research. For this region the GDP growth variable is the only variable that shows a significant relationship with the attraction of Dutch FDI in the analysis. Observation of the data used for the analysis for the South-American continent shows that the Netherlands Antilles forms an outlier (with a high impact on the observed relationship). Compared to its size, the Netherlands Antilles has relatively extremely high inflow of Dutch FDI. This high inflow of Dutch FDI to the Antilles could possibly be explained by the long historic relationships between The Netherlands and The Netherlands Antilles and the existing financial and tax advantages for Dutch MNEs on the Antilles. In order that get a better idea of the significance of this observation, more detailed data is required concerning the destination of this inflow of FDI from The Netherlands. From this analysis, it is not clear whether the FDI stays in the Antilles, whether it is used to fund further investments in other countries or whether there are other factors playing a role in this high flow of FDI. When more information is obtained on the possible reasons and final destinations of these investments, more substantially interesting conclusions can be derived from this observation.
Another notable observation is the fact that the relationship between Dutch outward FDI and growth rates of the European countries is not significant. This can mean that Dutch firms do no take this variable into account when investing in European countries. Another possible explanation might be that for Europe other factors like proximity, size, experience and the European Union outweigh the effect of the relatively low GDP growth rate of the most important western European countries.
Based on the outcomes of the research there is not enough proof to accept hypothesis 3 – a strong and positive relationship between Dutch outward FDI and a host country’s openness.
In recent years many nations launched an open door policy towards FDI in order to capture the growth enhancing effects of FDI on investments, employment, productivity and economic development in general. Becoming a more open economy in terms of trade does not necessarily mean that a country will at the same time attract more FDI. This raises a few questions. The main question is whether or not trade and FDI are in fact substitutes. Instead of performing FDI in a certain country, is producing domestically and exporting to that certain country the other option? In that sense, it can be argued that openness and FDI flows are not complements that go together but are substitutes. Dutch companies make a trade-off between whether to export to a country or whether to start a subsidiary company in that country. So when a country opens up its boarders and becomes a more open economy, Dutch firms feel more inclined to sell more of their products in that country rather than move abroad and start producing locally and serving the market from such a perspective.
This observation is particularly interesting in the case of the Netherlands, considering the fact that the service industry in the Netherlands plays such a big role in the economy. For service-oriented firms, there is a much greater need to be close to the consumer than in the case of manufactured goods. As manufactured goods can be easily traded, services are much less mobile and thus being close to the market is much more important. This distinction creates interesting options for future research. As openness in this study is measured by exports and imports as a fraction of GDP, a decrease in this variable suggests its more interesting for Dutch firms to enter such a market by means of FDI, although the statistical proof was insufficient.
Although this analysis does not give enough insight in this matter, this observation does create opportunities for further research. It could be of particular interest to observe whether changes in openness of a country are able to attract more Dutch FDI.
Of the control variables, the results on both distance and size variable indeed provide enough proof to correspond with the expectations. In terms of distance, the further away a country is, the less likely Dutch firms are willing to invest into that country. A possible explanation is that a mother company in the Netherlands will want to have a certain level of control over its investments worldwide. This becomes harder when firms are in different time zones across the globe which poses barriers to easy communication.
The physical size of a host country also influences Dutch companies FDI decisions. The effect of size could be the result of the amount of physical opportunities available in a country. A very small country like Singapore will create the possibility to open one or two subsidiaries, whilst a larger country such as Canada, the United States or Brazil (amongst others) is much more likely to create room for more opportunities. The larger the country, the more cities a company is able to target. This argument could especially hold true for The Netherlands since its relatively high dependency on the services industry. Consequently, these results are very much in line with the expectations on the variable.
The analysis did not, however, provide any proof on a relationship between the growth rate of the Dutch economy and outward FDI. This means that growth in the Dutch economy does not necessarily create an increased outflow of Dutch capital. Consequently, it appears that Dutch companies are just as likely to invest the extra profits at home rather then increasing the investments abroad.
SECTION 7: Conclusions
On a global scale, the flows of FDI are influenced by various micro- and macroeconomic factors. There are large amounts of research focused on the topic trying to explain the flows of capital from one country to another, with mixed results. Although this particular research has proven that a statistical relevant relationship exists between attraction of Dutch FDI and GDP per capita, WTO membership, the physical size of a host country and the distance between the Netherlands and the host country, there are still a large range of possible influences on these flows.
In this research, it was possible to accept two of the four hypotheses. A statistical significant positive relationship was found between the variables GDP per capita and WTO membership and the attraction of Dutch outward FDI. The dataset used for this research did not, however, provide enough evidence that Dutch firms take the factors GDP growth rates and host country’s openness into account when deciding in what country to invest. Consequently, it was not possible to accept the two hypotheses concerning these variables. As mentioned before and indicated in the general research on the topic of distribution of FDI a large range of influences might have been the cause of this.
Some of the variables included in this analysis have shown varying results in prior research on FDI flows. Comparing the results of this research to previous research will be very much of interest with respect to the previously found relationships and contribute to the discussion on them.
Past research has shown varying results on the influence of the GDP growth rate or GDP per capita of a country on attracting FDI. For example, Filippaios, Papanastassiou and Pearce (2003) observed a negative relationship between the attraction FDI and GDP per capita7 whereas Benassy-Quere, Coupet and Mayer (2005) find the relationship to be positive8. Economists on both sides are able to come up with proof and an explanation of their belief. The outcomes of this research focussing on the attraction of Dutch FDI in particular indicate a positive relationship; however the statistical relevance of the relationship with respect to GDP growth rates is too weak to be able to draw any conclusions based on the results.
7 For the US to the Pacific region of the OECD using a sample of 16 years 8
The results on the variable openness in this research seems quite ambiguous in relationship to the general opinion in the literature. The possible reasons and explanations behind these results have been discussed in section 5 of this paper. The general view of economists is that economies that trade also show high rates of inflow of FDI. The results of this research however contradict this opinion to a certain extent. As mentioned before, measurement issues might be the result of this though. Therefore, more insight is needed on the matter to obtain more accurate conclusions. The fact that the Netherlands show a negative correlation with the rest of Europe on this variable, could suggests that the low transportation costs within the European Union allow firms to export cheaply to the rest of the continent. It is not absolutely necessary to perform direct investments because of the low costs of exporting to near countries.
The fact that a statistical significant positive relationship was found between Dutch FDI outflow and WTO membership is in line with both the ideals and goals of the WTO, and the literature directed at the matter. Consequently, this is further proof of the positive functioning of the WTO and that it, at least to a certain extent, obtains its goals. As Dutch companies are very much dependant on foreign markets, the WTO is a good helping hand in providing more opportunities to them.
This research has, altogether, given a good insight on what some of the factors influencing FDI flows are and which ones indeed prove to be important determinants of the distribution of Dutch outward FDI.
It is important to note the impact of the uniqueness of the set used in this research. The data-set used in this research is much larger in scope than in general used in research on FDI. This data set includes a range of 49 host countries over a longitudinal time period of 20 years (1985 until 2005). Most prior studies use either a smaller time period, or a smaller amount of countries.
The use of a large sample of host countries from all continents of the world is done to level out country specific elements of the host countries. The objective of this research was to determine the predictive capacity of the 4 variables (namely GDP growth, GDP per capita, openness and WTO membership) on the distribution of Dutch FDI to any country.
A suggestion for further research might be to use a different measure for openness. The fact that openness measured by exports + imports/ GDP gives such different results over different geographical regions indicates a need for further research. Can it be proven that when openness is measured in a different way the result of the analysis are more congruent across all geographical regions or is it necessary to delve deeper in what drives a country’s openness to be able to find an explanation to the observed phenomenon? The United States is a very large trading country, though still it is relatively closed in terms of exports + imports/ GDP. This is definitely worth investigating.
Another suggestion for further research could be to analyse the determinants of Dutch FDI per type of industry. I would predict that the importance of the variables differs across industries; for example for the electronics industry an agglomeration criteria could be of higher importance and for the banking industry level of development of an economy would be of higher importance. Running this analysis could shed more light of specific requirements of different industries. Last but not least, a deeper analysis into a lagged FDI/ experience variable could give very interesting results. In this sense, a country could have a historical relationship for a period of longer than 100 years making it more likely for a country to invest in it. Does that have any additional influences? Relating that point to this analysis, the relationship between the Netherlands and Suriname and the Netherlands Antilles for example might prove to provide interesting results.
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Data sources
De Nederlandse Bank, www.dnb.nl
The International Monetary Fund, www.imf.org
APPENDICES
Countries used in the analysis per continent
Africa Europe North America
Egypt Austria Canada
Ghana Czech Republic Mexico
Nigeria Denmark United States
South-Africa Finland
France South America
Asia Germany incl. former DDR Argentina
Australia Greece Brazil
China Hungary Chile
Hong Kong Ireland Colombia
India Italy Netherlands Antilles
Indonesia Norway Peru
Israel Poland Suriname
Japan Portugal
Korea Romania
Malaysia Spain
New Zealand Sweden
Philippines Switzerland
Saudi Arabia Turkey
Singapore United Kingdom
Taiwan Thailand
Figure 1.1: world outward FDI (in billion $)
Source: UNCTAD statistical database
Figure 1.2: % of world FDI inward stock per region over time
0 5 10 15 20 25 30 35 40 45 50 % world inward FDI stock
Developed economies Developing economies
America Asia Europe Oceania Africa America Asia
Data series: 1980 1990 2000 Source: www.unctad.org 0 5 10 15 20 25 30 35 40 45 50 % world inward FDI stock
Developed economies Developing economies
America Asia Europe Oceania Africa America Asia
Data series: 1980 1990 2000 0 5 10 15 20 25 30 35 40 45 50 % world inward FDI stock
Developed economies Developing economies
America Asia Europe Oceania Africa America Asia
Data series: 1980 1990 2000 % world inward FDI stock
Developed economies Developing economies
America Asia Europe Oceania Africa America Asia
America Asia Europe Oceania Africa America Asia
Data series: 1980 1990 2000
Figure 1.3: % of world FDI inward flow per region over time
Figure 1.4: Outward FDI as a % of GDP
0 1 0 2 0 3 0 4 0 5 0 6 0
A m erica A sia E urope O ceania Africa A m erica Asia
D evelo ped econom ies D eveloping econom ie s
% w orld inward F D I flo w D ata serie s: 1980 1990 2000 S ource: w w w .unctad.org 0 1 0 2 0 3 0 4 0 5 0 6 0
A m erica A sia E urope O ceania Africa A m erica Asia
D evelo ped econom ies D eveloping econom ie s
% w orld inward F D I flo w D ata serie s: 1980 1990 2000 S ource: w w w .unctad.org
A m erica A sia E urope O ceania Africa A m erica Asia
A m erica A sia E urope O ceania Africa A m erica Asia
D evelo ped econom ies D eveloping econom ie s
Figure 2.1: Dutch outward service FDI as a % of total outward FDI 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
